BACKGROUND:
Drug policy has traditionally relied on deterrence-based models that assume rational responses to prices, sanctions, and enforcement. However, illicit drug markets persist despite intensified repression, suggesting a mismatch between policy design and actual decision-making under conditions of addiction, scarcity, and social marginalization. Behavioral economics offers a framework for understanding this failure by focusing on how environments shape choices rather than assuming stable preferences.

OBJECTIVE:
This presentation reframes drug-assisted treatment (DAT) as a behavioral policy intervention that operates through choice architecture rather than pharmacological substitution. Using heroin-assisted treatment as a case study, it examines the behavioral mechanisms through which institutionalized access alters decision-making and reduces harm. Methods / Conceptual framework: Drawing on behavioral economics and policy design literature, we analyze DAT through three mechanisms: (1) reframing losses and gains, (2) reducing cognitive load, and (3) embedding behavior in institutional commitment devices. These mechanisms are contrasted with the volatility and uncertainty of illicit drug markets, which amplify present bias, risk-taking, and myopic decision-making. Results / Key insights: Heroin-assisted treatment replaces market volatility with institutional predictability, stabilizing perceived risk, reducing cognitive burden, and lowering the behavioral costs of safer choices without coercion. Evidence from Switzerland shows that these design features translate into sustained reductions in illicit drug use, criminal involvement, and social marginalization—effects that cannot be explained by pharmacology alone. Implications: Understanding DAT as choice architecture clarifies its effectiveness and strengthens its policy relevance. This perspective also provides a conceptual basis for considering cocaine-assisted treatment as a logical extension of existing harm reduction infrastructure, rather than a radical pharmacological innovation.

CONCLUSIONS:
Behavior change in addiction policy is achieved most reliably not by increasing punishment or information, but by redesigning environments. Drug-assisted treatment illustrates how behavioral policy design can outperform deterrence in contexts of scarcity, volatility, and constrained choice.